
> # set up environment ----
> library(data.table)
data.table 1.14.3 IN DEVELOPMENT built 2022-03-16 16:23:36 UTC; root using 4 threads (see ?getDTthreads).  Latest news: r-datatable.com
**********
This development version of data.table was built more than 4 weeks ago. Please update: data.table::update.dev.pkg()
**********

> library(ggplot2)

> library(Hmisc)
Loading required package: lattice
Loading required package: survival
Loading required package: Formula

Attaching package: ‘Hmisc’

The following objects are masked from ‘package:base’:

    format.pval, units


> library(gridExtra)

> source("R/00-functions.R")

> load("data/analysis_data.RData")

> theme_set(
+   theme_bw() +
+     theme(
+       legend.position = "bottom",
+       legend.title = element_blank(),
+       plot.title = element_text(hjust = .5, size = 14),
+       strip.background = element_rect(fill = NA, color = NA)))

> # equivalence testing ----
> X <- copy(respondent_data)

> equivalence_test <- run_equiv(
+   X = X[, .(
+     `Age 18-24` = as.numeric(age_category == "18-24"),
+     `Age 25-34` = as.numeric(age_category == "25-34"),
+     `Age 35-44` = as.numeric(age_category == "35-44"),
+     `Age 45-64` = as.numeric(age_category == "45-64"),
+     `Age Over 65` = as.numeric(age_category == "Over 65"),
+     `Did not Vote/Supp. Other Cand. in 2016` = as.numeric(support_2016 == "other/no one"),
+     `Supported Clinton in 2016` = as.numeric(support_2016 == "Clinton"),
+     `Supported Sanders in 2016` = as.numeric(support_2016 == "Sanders"),
+     `Supported Trump in 2016` = as.numeric(support_2016 == "Trump"),
+     `HS or Less` = as.numeric(education == "HS or Less"),
+     `Some College` = as.numeric(education == "Some College"),
+     `College Graduate` = as.numeric(education == "College Grad."),
+     `Black` = as.numeric(race_ethnicity == "Black"),
+     `Latino` = as.numeric(race_ethnicity == "Latino"),
+     `Other/Mixed Race/Ethnicity` = as.numeric(race_ethnicity == "Other/Mixed"),
+     `White` = as.numeric(race_ethnicity == "White"),
+     `Female` = female,
+     `Campaign Knowledge` = campaign_knowledge,
+     `Follows Politics` = follows_politics,
+     `Strong Democrat` = strong_democrat,
+     `Trump Least Preferred` = trump_least_preferred,
+     `Intend to Vote` = vote_2020,
+     `Registered Voter` = registered_voter,
+     Ideology = ideology,
+     `Political Interest` = political_interest,
+     `# Failed Attention Checks` = n_attention_fails,
+     `Need for Cognition` = need_for_cognition)],
+   Tr = X[, electability_last],
+   w = rep(1, nrow(X)),
+   epsilon.method = "strict",
+   fdr_correct = TRUE)

> cairo_pdf("figures/balance-full-dataset.pdf", height = 6.5, width = 12)

> generate_plot(equivalence_test, display.names = equivalence_test$display.names,
+   panel.widths = c(3, 1, 5, 1, 1),
+   var.rounding = 2, pval.rounding = 2,
+   title_text = "Equivalence Tests of Covariate Balance, Main Dataset (n = 1211)")
[1] 0
[1] "here"
NULL
Loading required package: cowplot

> dev.off()
null device 
          1 

> X <- copy(respondent_data[trump_least_preferred == 1 & support_2016 != "Trump" & n_attention_fails <= 1])

> equivalence_test <- run_equiv(
+   X = X[, .(
+     `Age 18-24` = as.numeric(age_category == "18-24"),
+     `Age 25-34` = as.numeric(age_category == "25-34"),
+     `Age 35-44` = as.numeric(age_category == "35-44"),
+     `Age 45-64` = as.numeric(age_category == "45-64"),
+     `Age Over 65` = as.numeric(age_category == "Over 65"),
+     `Did not Vote/Supp. Other Cand. in 2016` = as.numeric(support_2016 == "other/no one"),
+     `Supported Clinton in 2016` = as.numeric(support_2016 == "Clinton"),
+     `Supported Sanders in 2016` = as.numeric(support_2016 == "Sanders"),
+     # `Supported Trump in 2016` = as.numeric(support_2016 == "Trump"),
+     `HS or Less` = as.numeric(education == "HS or Less"),
+     `Some College` = as.numeric(education == "Some College"),
+     `College Graduate` = as.numeric(education == "College Grad."),
+     `Black` = as.numeric(race_ethnicity == "Black"),
+     `Latino` = as.numeric(race_ethnicity == "Latino"),
+     `Other/Mixed Race/Ethnicity` = as.numeric(race_ethnicity == "Other/Mixed"),
+     `White` = as.numeric(race_ethnicity == "White"),
+     `Female` = female,
+     `Campaign Knowledge` = campaign_knowledge,
+     `Follows Politics` = follows_politics,
+     `Strong Democrat` = strong_democrat,
+     # `Trump Least Preferred` = trump_least_preferred,
+     `Intend to Vote` = vote_2020,
+     `Registered Voter` = registered_voter,
+     Ideology = ideology,
+     `Political Interest` = political_interest,
+     `# Failed Attention Checks` = n_attention_fails,
+     `Need for Cognition` = need_for_cognition)],
+   Tr = X[, electability_last],
+   w = rep(1, nrow(X)),
+   epsilon.method = "strict",
+   fdr_correct = TRUE)

> cairo_pdf("figures/balance-main-dataset.pdf", height = 6.5, width = 12)

> generate_plot(equivalence_test, display.names = equivalence_test$display.names,
+   panel.widths = c(3, 1, 5, 1, 1),
+   var.rounding = 2, pval.rounding = 2,
+   title_text = "Equivalence Tests of Covariate Balance, Main Dataset (n = 833)")
[1] 0
[1] "here"
NULL

> dev.off()
null device 
          1 
